verticapy.vDataColumn.value_counts#

vDataColumn.value_counts(k: int = 30) → TableSample#

This function returns the k most frequently occurring elements in a column, along with information about how often they occur. Additionally, it provides various statistical details to give you a comprehensive view of the data distribution.

Parameters#

k: int, optional: Number of most occurent elements to return.

Returns#

TableSample: result.

Examples#

For this example, we will use the following dataset:

import verticapy as vp

data = vp.vDataFrame(
    {
        "x": [1, 2, 4, 9, 10, 15, 20, 22],
        "y": [1, 2, 1, 2, 1, 1, 2, 1],
        "z": [10, 12, 2, 1, 9, 8, 1, 3],
    }
)

Now, let’s calculate the values and counts for a specific column.

data["x"].value_counts(k = 6)

	value
name	"x"
dtype	integer
unique	8.0
count	8.0
9	1
10	1
1	1
4	1
2	1
15	1
Others	1

Note

All the calculations are pushed to the database.

Hint

For more precise control, please refer to the aggregate method.